Modelo de simulación del COVID-19 basado en agentes. Aplicación al caso argentino
The model presented is a multi-agent simulation that visualizes the emerging dynamics of the interaction and influence of a subset of biological and social factors in the development of the COVID-19 pandemic. The model is implemented in NetLogo (programming language and simulation environm...
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| Autores principales: | , , |
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| Formato: | Artículo acceptedVersion Artículo |
| Lenguaje: | Español Español |
| Publicado: |
Instituto de Investigaciones Geográficas. Universidad Nacional de Luján
2020
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| Materias: | |
| Acceso en línea: | http://ri.unlu.edu.ar/xmlui/handle/rediunlu/687 |
| Aporte de: |
| Sumario: | The model presented is a multi-agent simulation that visualizes the emerging dynamics of the interaction and influence of a subset of biological and social factors in the development of the COVID-19 pandemic. The model is implemented in NetLogo (programming language and simulation environment, adapted to simulate phenomena involving multiple agents interacting).The objective is to simulate, through a didactic approach, different hypothetical scenarios adjusting demographic, medical, social and institutional parameters associated with the evolution and spread of the virus. Four evolution scenarios of COVID19 in Argentina were analyzed, with different levels of restriction in population mobility. Expressed in number of days with partial quarantine, they were: E1 90 days, E2 0 days, E3 63 days and E4 48 days, during a simulation of 90 consecutive days.The model made it possible to operationalize the way in which different variables interact with each other. This makes it possible to simulate in a multidimensional context the non-linear effect of explanatory variables on the evolution of COVID-19. Social isolation is, in all cases, the measure that most affects the behavior of the spread of the virus, therefore, the one that most helps to prevent and slow down the spread. |
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